Detecting obstacles in the environment of a vehicle becomes important, for instance, in advanced driver assistance systems (“ADAS”). There are currently different approaches for detecting obstacles in images. For example, stereo cameras, ultrasound or equivalent detection means enable reliable estimation of a three-dimensional environment. However, this approach requires complex and expensive hardware. Alternatively, monocular approaches may be used for detecting obstacles. For instance, static approaches may detect objects within a single image by using assumptions about properties of an object. However, these assumptions often fail. Further, a structure from motion (“SFM”) may be used for estimating three-dimensional properties of an image. These approaches rely on the assumption that the objects in a scene are static. Otherwise, the objects become unpredictable if the scene is not static. Hence, these assumptions are not very reliable and require high computational costs.
As such, it is desirable to present an improved approach for detecting objects in an image. In particular, there is a need for a reliable detecting of objects in images captured by a monocular camera. In addition, other desirable features and characteristics will become apparent from the subsequent summary and detailed description, and the appended claims, taken in conjunction with the accompanying drawings and this background.